



from argparse import ArgumentParser

from . import BaseTransformersCLICommand






def 							A							(   _lowerCamelCase    ):





							'''simple docstring'''




							return DownloadCommand(args.model							,					args.cache_dir							,					args.force							,					args.trust_remote_code    )



class     UpperCAmelCase_       (			__lowercase):







							@staticmethod
							def   snake_case__ (  __a):

														'''simple docstring'''

														_lowerCAmelCase	:				Union[str, Any]					  =       parser.add_parser("download")
														download_parser.add_argument(
														    "--cache-dir",     type=__a,     default=__a,     help="Path to location to store the models")
														download_parser.add_argument(
														    "--force",     action="store_true",     help="Force the model to be download even if already in cache-dir")
														download_parser.add_argument(
														    "--trust-remote-code",     action="store_true",     help="Whether or not to allow for custom models defined on the Hub in their own modeling files. Use only if you've reviewed the code as it will execute on your local machine",     )
														download_parser.add_argument("model",     type=__a,     help="Name of the model to download")
														download_parser.set_defaults(func=__a)







							def __init__(  self,     __a,     __a,     __a,     __a):

														'''simple docstring'''

														_lowerCAmelCase	:				Optional[int]					  =       model
														_lowerCAmelCase	:				int					  =       cache
														_lowerCAmelCase	:				List[str]					  =       force
														_lowerCAmelCase	:				int					  =       trust_remote_code







							def   snake_case__ (  self):

														'''simple docstring'''

														from ..models.auto import AutoModel, AutoTokenizer

														AutoModel.from_pretrained(
														    self._model,     cache_dir=self._cache,     force_download=self._force,     trust_remote_code=self._trust_remote_code)
														AutoTokenizer.from_pretrained(
														    self._model,     cache_dir=self._cache,     force_download=self._force,     trust_remote_code=self._trust_remote_code)


import os
from shutil import copyfile
from typing import List, Optional, Tuple

from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging


if is_sentencepiece_available():
		from .tokenization_fnet import FNetTokenizer
else:
		lowercase    :   List[Any]						=			None

lowercase    :   Tuple						=			logging.get_logger(__name__)
lowercase    :   Optional[Any]						=			{'vocab_file': 'spiece.model', 'tokenizer_file': 'tokenizer.json'}

lowercase    :   str						=			{
    'vocab_file': {
        'google/fnet-base': 'https://huggingface.co/google/fnet-base/resolve/main/spiece.model',
        'google/fnet-large': 'https://huggingface.co/google/fnet-large/resolve/main/spiece.model',
    },
    'tokenizer_file': {
        'google/fnet-base': 'https://huggingface.co/google/fnet-base/resolve/main/tokenizer.json',
        'google/fnet-large': 'https://huggingface.co/google/fnet-large/resolve/main/tokenizer.json',
    },
}

lowercase    :   int						=			{
    'google/fnet-base': 512,
    'google/fnet-large': 512,
}

lowercase    :   str						=			'▁'




class 					lowerCamelCase__				(							__lowercase):




	'''simple docstring'''




	_A								=	VOCAB_FILES_NAMES
	_A								=	PRETRAINED_VOCAB_FILES_MAP
	_A								=	PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
	_A								=	['input_ids', 'token_type_ids']
	_A								=	FNetTokenizer







	def __init__(   self						:Optional[int]	,  a						:Union[str, Any]=None	,  a						:Optional[int]=None	,  a						:str=False	,  a						:Tuple=True	,  a						:Optional[Any]=True	,  a						:Optional[int]="<unk>"	,  a						:List[str]="[SEP]"	,  a						:Optional[Any]="<pad>"	,  a						:int="[CLS]"	,  a						:Dict="[MASK]"	,  **a						:Optional[int]	,  )						->					List[str]:
								# Mask token behave like a normal word, i.e. include the space before it and
								# is included in the raw text, there should be a match in a non-normalized sentence.
								__UpperCamelCase      :  List[Any]       =   (
								    AddedToken(a	,  lstrip=a	,  rstrip=a	,  normalized=a		)
								    if isinstance(a	,  a		)
								    else mask_token
								)

								super().__init__(
								    a	,  tokenizer_file=a	,  do_lower_case=a	,  remove_space=a	,  keep_accents=a	,  unk_token=a	,  sep_token=a	,  pad_token=a	,  cls_token=a	,  mask_token=a	,  **a	,  )

								__UpperCamelCase      :  List[Any]       =   do_lower_case
								__UpperCamelCase      :  str       =   remove_space
								__UpperCamelCase      :  Dict       =   keep_accents
								__UpperCamelCase      :  Union[str, Any]       =   vocab_file
								__UpperCamelCase      :  List[str]       =   False if not self.vocab_file else True







	def   _lowerCamelCase							(   self						:Dict	,  a						:List[int]	,  a						:Optional[List[int]] = None		)						->					List[int]:
								__UpperCamelCase      :  List[str]       =   [self.sep_token_id]
								__UpperCamelCase      :  List[str]       =   [self.cls_token_id]
								if token_ids_a is None:
															return cls + token_ids_a + sep
								return cls + token_ids_a + sep + token_ids_a + sep







	def   _lowerCamelCase							(   self						:Union[str, Any]	,  a						:List[int]	,  a						:Optional[List[int]] = None		)						->					List[int]:
								__UpperCamelCase      :  List[Any]       =   [self.sep_token_id]
								__UpperCamelCase      :  List[Any]       =   [self.cls_token_id]

								if token_ids_a is None:
															return len(cls + token_ids_a + sep		) * [0]
								return len(cls + token_ids_a + sep		) * [0] + len(token_ids_a + sep		) * [1]







	def   _lowerCamelCase							(   self						:int	,  a						:str	,  a						:Optional[str] = None		)						->					Tuple[str]:
								if not os.path.isdir(a		):
															logger.error(f'Vocabulary path ({save_directory}) should be a directory'		)
															return
								__UpperCamelCase      :  str       =   os.path.join(
								    a	,  (filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"]		)

								if os.path.abspath(self.vocab_file		) != os.path.abspath(a		):
															copyfile(self.vocab_file	,  a		)

								return (out_vocab_file,)